Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Jose Costa Pereira"'
Publikováno v:
International Journal of Computer Vision. 129:419-438
Image hash codes are produced by binarizing the embeddings of convolutional neural networks (CNN) trained for either classification or retrieval. While proxy embeddings achieve good performance on both tasks, they are non-trivial to binarize, due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba9ba1d35af360f76c9637b58938b2c3
https://doi.org/10.1007/s11263-020-01362-7
https://doi.org/10.1007/s11263-020-01362-7
Publikováno v:
Medical Image Analysis. 83:102690
Breast cancer is the most common and lethal form of cancer in women. Recent efforts have focused on developing accurate neural network-based computer-aided diagnosis systems for screening to help anticipate this disease. The ultimate goal is to reduc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0330f566e8fe43e43c38bd6d64ff532b
https://doi.org/10.1016/j.media.2022.102690
https://doi.org/10.1016/j.media.2022.102690
Autor:
Wassim Hamidouche, Byungyeon Kang, Shuwei Shi, Yujiu Yang, Junlin Li, Pengfei Sun, Jose Costa Pereira, Kele Xu, Hiroaki Akutsu, Hai Wang, Koki Tsubota, Yiting Liao, William Thong, Hengliang Luo, Longtao Feng, Jingyu Guo, Yuqing Hou, Yu Qiao, Sung-Jun Yoon, Jimmy Ren, Tao Zhang, Yang Li, Bin Yi, Yifan Chen, Jinjin Gu, Ali Royat, Steven McDonagh, Shuhang Gu, Junwoo Lee, Kiyoharu Aizawa, Lehan Yang, Sewoong Ahn, Weihao Xia, Qingyan Bai, Haiyang Guo, Zirui Wang, Mingdeng Cao, Qing Zhang, Jiahao Wang, Wenming Yang, Sid Ahmed Fezza, Haoming Cai, Dounia Hammou, Ales Leonardis, Radu Timofte, Hengxing Cai, Manri Cheon, Seyed Mehdi Ayyoubzadeh, Chao Dong, Gwangjin Yoon
Publikováno v:
CVPR Workshops
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021. As a new type of image processing techno
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cd2eb5a3a1d660da7fb6cd6f60817a6
https://doi.org/10.1109/cvprw53098.2021.00077
https://doi.org/10.1109/cvprw53098.2021.00077
Publikováno v:
IJCNN
Web of Science
Web of Science
A key to the generalization ability of Convolutional Neural Networks (CNNs) is the idea that patterns that appear in one region of the image have a high probability of appearing in other regions. This notion is also true for other spatial relationshi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6cd155265be20e6e3f1de5d1f1b6c7c3
https://doi.org/10.1109/ijcnn48605.2020.9206640
https://doi.org/10.1109/ijcnn48605.2020.9206640
Publikováno v:
EMBC
Convolutional Neural Networks (CNN) have become the gold standard in many visual recognition tasks including medical applications. Due to their high variance, however, these models are prone to over-fit the data they are trained on. To mitigate this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::884aab3657be6c760cb1a1839afb011e
https://pubmed.ncbi.nlm.nih.gov/31946316
https://pubmed.ncbi.nlm.nih.gov/31946316
Autor:
Hyo-Eun Kim, Jiashi Feng, Stephen H. Friend, Ljubomir Buturovic, Dezső Ribli, Luis Caballero, Li Shen, Fredrik Strand, Yaroslav Nikulin, Krzysztof J. Geras, Kyunghyun Cho, Elias Chaibub Neto, Rami Ben-Ari, Christoph I. Lee, Zequn Jie, Imane Nedjar, Felix Nensa, Darvin Yi, Shivanthan A.C. Yohanandan, Bruce Hoff, Justin Guinney, Jaime S. Cardoso, Russell B. McBride, Mengling Feng, Yiqiu Shen, Simona Rabinovici-Cohen, Ethan Goan, Stefan Harrer, Sven Koitka, Michael Kawczynski, Hari Trivedi, Karl Trygve Kalleberg, Christoph M. Friedrich, F. Albiol, Dimitri Perrin, Jose Costa Pereira, Umar Asif, Bibo Shi, Zbigniew Wojna, Antonio Jimeno Yepes, Peter Lindholm, Berkman Sahiner, Sijia Wang, Thea Norman, Weiva Sieh, Joyce Cahoon, Gerard Cardoso Negrie, Pavitra Krishnaswamy, Diana S. M. Buist, Alberto Albiol, Lester Mackey, Hwejin Jung, Laurie R. Margolies, Gaurav Pandey, Can Son Khoo, William Lotter, Yuanfang Guan, Thomas Yu, Andrew D. Trister, Stephen Morrell, Gustavo Stolovitzky, A. Gregory Sorensen, Clinton Fookes, Mehmet Eren Ahsen, David D. Cox, Jae Ho Sohn, Hao Du, Thomas Schaffter, Joseph H. Rothstein, Eduardo Castro, Joseph Y. Lo, Daniel L. Rubin, Obioma Pelka
Publikováno v:
JAMA Network Open
Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evalua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c12077daf27f336825279d2831286b1
https://doi.org/10.1001/jamanetworkopen.2020.0265
https://doi.org/10.1001/jamanetworkopen.2020.0265
Publikováno v:
BHI
Two limitations hamper performance of deep architectures for classification and/or detection in medical imaging: (i) the small amount of available data, and (ii) the class imbalance scenario. While millions of labeled images are available today to bu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29d32be00fc547f149c583ff8a5e2f2d
https://doi.org/10.1109/bhi.2018.8333411
https://doi.org/10.1109/bhi.2018.8333411
Publikováno v:
ICASSP
This paper addresses the problem of document retrieval based on sentiment polarity criteria. A query based on natural spontaneous speech, expressing an opinion about a certain topic, is used to search a repository of documents containing favorable or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bb3a5601a8ff6d4f8b1537b646a5a60
https://doi.org/10.1109/icassp.2014.6854470
https://doi.org/10.1109/icassp.2014.6854470
Autor:
Jose Costa Pereira, Emanuele Coviello, Nikhil Rasiwasia, Gabriel Doyle, Nuno Vasconcelos, Roger Levy, Gert R. G. Lanckriet
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence, vol 36, iss 3
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Costa Pereira, J; Coviello, E; Doyle, G; Rasiwasia, N; Lanckriet, GRG; Levy, R; et al.(2013). On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval.. IEEE transactions on pattern analysis and machine intelligence. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/2th7x68p
Costa Pereira, J; Coviello, E; Doyle, G; Rasiwasia, N; Lanckriet, GRG; Levy, R; et al.(2014). On the role of correlation and abstraction in cross-modal multimedia retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(3), 521-535. doi: 10.1109/TPAMI.2013.142. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/28w847tt
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Costa Pereira, J; Coviello, E; Doyle, G; Rasiwasia, N; Lanckriet, GRG; Levy, R; et al.(2013). On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval.. IEEE transactions on pattern analysis and machine intelligence. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/2th7x68p
Costa Pereira, J; Coviello, E; Doyle, G; Rasiwasia, N; Lanckriet, GRG; Levy, R; et al.(2014). On the role of correlation and abstraction in cross-modal multimedia retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(3), 521-535. doi: 10.1109/TPAMI.2013.142. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/28w847tt
The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, for example, using an image to search for texts. A mathematical fo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8b847d20614a061eb53c2ea4ec25b9e
https://escholarship.org/uc/item/28w847tt
https://escholarship.org/uc/item/28w847tt
Autor:
Nuno Vasconcelos, Jose Costa Pereira
Publikováno v:
Costa Pereira, J; & Vasconcelos, N. (2014). Cross-modal domain adaptation for text-based regularization of image semantics in image retrieval systems. Computer Vision and Image Understanding, 124, 123-135. doi: 10.1016/j.cviu.2014.03.003. UC San Diego: Retrieved from: http://www.escholarship.org/uc/item/23f6v6hc
Computer Vision and Image Understanding, vol 124
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Computer Vision and Image Understanding, vol 124
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
In query-by-semantic-example image retrieval, images are ranked by similarity of semantic descriptors. These descriptors are obtained by classifying each image with respect to a pre-defined vocabulary of semantic concepts. In this work, we consider t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12b4c29e14711ea7870f781d7f8de113
http://www.escholarship.org/uc/item/23f6v6hc
http://www.escholarship.org/uc/item/23f6v6hc